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 normal orthogonal system 的翻译结果: 查询用时：0.173秒
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 normal orthogonal system 就范正交系(0)标准正交系(2)
 标准正交系
 We develep a new training method in which a normal orthogonal system is used as sample. 提出了采用标准正交系作为样本的新的训练方法 . 短句来源 After training according to this method,the output of the neural network can approximate uniform state of the linear time varying system on the subspace of L 2([0,t 1];R m) spun by this normal orthogonal system. 按照这种方法训练后 ,在由这个标准正交系所生成的 L2 ([0 ,t1 ];Rm)的子空间上 ,神经网络的输出一致逼近线性时变系统的状态 短句来源
 “normal orthogonal system”译为未确定词的双语例句
 Using the Elementary Line Transformation of Matrix Extract the Normal Orthogonal System of Solution of Homogeneous Linear System of Equations 用矩阵的初等行变换求齐次线性方程组的标准正交解系 短句来源
 相似匹配句对
 Application of orthogonal transformation on normal population 正交变换在正态总体中的应用 短句来源 CORRECTED ORTHOGONAL ELECTROCARDIOGRAM IN NORMAL POPULATION 正常人正交导联心电图QRS波 短句来源 normal group. E、西药对照组(心律平组)。 短句来源 THE ORTHOGONAL TRANSFORMATION 正交变换另析 短句来源 On Normal Education 试论师范专科教育 短句来源

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 In this paper a method is put forward to extract the normal orthogonal system of solution of homogeneous linear system of equations using the elementary line transformation of matrix. This method joins extracting the basic solution system of linear system of equations to standardizing the basic solution system,so that it is simpler and more direct,and it is more convenient to make numerical calculation with computer programming. 提出一个用矩阵的初等变换求线性方程组的解空间的标准正交基的方法。该方法将求线性方程组的基解向量与基解向量标准化连系起来,因而更为简捷,更便于编程序上计算机作数值计算。 This paper presents a neural network which can be used to identify linear time varying systems.The capatility of approximating linear time varying control systems on this neural network is studied.On any control functions set which is the bounded subset of L 2([0,t 1];R m),the neural network has the capatility of approximating uniform state of the linear time varying systems.We develep a new training method in which a normal orthogonal system is used as sample.After training according to this method,the... This paper presents a neural network which can be used to identify linear time varying systems.The capatility of approximating linear time varying control systems on this neural network is studied.On any control functions set which is the bounded subset of L 2([0,t 1];R m),the neural network has the capatility of approximating uniform state of the linear time varying systems.We develep a new training method in which a normal orthogonal system is used as sample.After training according to this method,the output of the neural network can approximate uniform state of the linear time varying system on the subspace of L 2([0,t 1];R m) spun by this normal orthogonal system. 构造了一种用于线性时变系统辨识的神经网络 ,研究了它对线性时变控制系统的逼近能力 .在以 L2 ([0 ,t1 ];Rm)的任意一个有界子集为控制函数集上 ,神经网络具有一致逼近线性时变系统的状态的能力 .提出了采用标准正交系作为样本的新的训练方法 .按照这种方法训练后 ,在由这个标准正交系所生成的 L2 ([0 ,t1 ];Rm)的子空间上 ,神经网络的输出一致逼近线性时变系统的状态
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